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A Panel Data Toolbox for MATLAB

Author

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  • Álvarez, Inmaculada C.
  • Barbero, Javier
  • Zofío, José L.

Abstract

Panel Data Toolbox is a new package for MATLAB that includes functions to estimate the main econometric methods of balanced and unbalanced panel data analysis. The package includes code for the standard fixed, between and random effects estimation methods, as well as for the existing instrumental panels and a wide array of spatial panels. A full set of relevant tests is also included. This paper describes the methodology and implementation of the functions and illustrates their use with well-known examples. We perform numerical checks against other popular commercial and free software to show the validity of the results.

Suggested Citation

  • Álvarez, Inmaculada C. & Barbero, Javier & Zofío, José L., 2017. "A Panel Data Toolbox for MATLAB," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 76(i06).
  • Handle: RePEc:jss:jstsof:v:076:i06
    DOI: http://hdl.handle.net/10.18637/jss.v076.i06
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    References listed on IDEAS

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    20. Baltagi, Badi H. & Liu, Long, 2009. "A note on the application of EC2SLS and EC3SLS estimators in panel data models," Statistics & Probability Letters, Elsevier, vol. 79(20), pages 2189-2192, October.
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    Cited by:

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    2. Ding Luo & Oded Cats & Hans Lint, 2020. "Can passenger flow distribution be estimated solely based on network properties in public transport systems?," Transportation, Springer, vol. 47(6), pages 2757-2776, December.
    3. Peter Nannestad, 2019. "Strategic Tax-Setting in Danish Municipalities? A First Look at the Evidence 2007 - 2017," Economics Working Paper from Condorcet Center for political Economy at CREM-CNRS 2019-10-ccr, Condorcet Center for political Economy.
    4. Gizem Umut Doğan & Gizem Umut Doğan, Aslıhan Kabadayı, 2015. "Determinants of Internal Migration in Turkey: A Panel Data Analysis Approach," Border Crossing, Transnational Press London, UK, vol. 2015(1502), pages 16-24, May.
    5. Álvarez, Inmaculada C. & Barbero, Javier & Zofío, José L., 2016. "A spatial autoregressive panel model to analyze road network spillovers on production," Transportation Research Part A: Policy and Practice, Elsevier, vol. 93(C), pages 83-92.
    6. Vlad-Cosmin Bulai & Alexandra Horobeț, 2019. "Is The Oil Price a Determinant of Employment in Oil Intensive Romanian Communities?," International Journal of Business and Economic Sciences Applied Research (IJBESAR), International Hellenic University (IHU), Kavala Campus, Greece (formerly Eastern Macedonia and Thrace Institute of Technology - EMaTTech), vol. 12(3), pages 7-13, December.
    7. Marcos Herrera & Jesus Mur & Manuel Ruiz-Marin, 2017. "A Comparison Study on Criteria to Select the Most Adequate Weighting Matrix," Working Papers 18, Instituto de Estudios Laborales y del Desarrollo Económico (IELDE) - Universidad Nacional de Salta - Facultad de Ciencias Económicas, Jurídicas y Sociales.
    8. Arash Nayebyazdi, 2017. "The Relationship Between Democracy And Economic Growth In Muslim Mena Countries (Spatial Econometric Approach)," Journal of Smart Economic Growth, , vol. 2(3), pages 123-155, December.
    9. Gizem Umut Doğan & Gizem Umut Doğan, Aslıhan Kabadayı, 2015. "Determinants of Internal Migration in Turkey: A Panel Data Analysis Approach," Border Crossing, Transnational Press London, UK, vol. 5(1-2), pages 16-24, January-J.
    10. Raphael Asada & Tamás Krisztin & Fulvio di Fulvio & Florian Kraxner & Tobias Stern, 2020. "Bioeconomic transition?: Projecting consumption‐based biomass and fossil material flows to 2050," Journal of Industrial Ecology, Yale University, vol. 24(5), pages 1059-1073, October.
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    More about this item

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation

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